Unified theories of cognition
Adaptation in natural and artificial systems
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Representational effects in a simple classifier system
SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
Lazy Learning of Bayesian Rules
Machine Learning
A hybrid genetic hill-climbing algorithm for four-coloring map problems
Design and application of hybrid intelligent systems
When a genetic algorithm outperforms hill-climbing
Theoretical Computer Science
Not So Naive Bayes: Aggregating One-Dependence Estimators
Machine Learning
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Automatic rule discovery and generalization in supervised and unsupervised learning tasks
Automatic rule discovery and generalization in supervised and unsupervised learning tasks
Rule induction based-on coevolutionary algorithms for image annotation
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
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EvRFind is an application used for the task of rule discovery in data mining. This paper describes various techniques used by EvRFind to enhance an evolutionary search for the purpose of rule discovery. Although some of the techniques are non-evolutionary by design, these still rely on evolution to guide the process. Results of experiments are compared to those found in other published work.